Improvements in Techniques and Approaches Energize a Once Stagnant Field

Personalized medicine, the application of genomic and molecular data to better target disease states, has been defined as a novel therapeutic concept for over a decade. At CHI’s “Molecular Medicine Tri Conference,” held recently in San Francisco, presenters demonstrated how the early promise of personalized medicine in cancer molecular diagnostics is now being realized.

Tumor model development has three specific challenges—genetic alterations, correct tissue context, and variation—all important in matching up drug response and genetic context. Current xenograft models have variation and alterations but are typically not well characterized. To address these shortcomings, AVEO Pharmaceuticals created a population-based tumor model system based on human-in-mouse tissue transgenic human tumors that feature naturally occurring tumor variation akin to that observed in human tumor populations. The consequence is that tumors vary from one to another, just like human tumors.

“Cell-line derived xenografts have not been good predictors of response in the clinic and, therefore, present big challenges for biomarker discovery,” said Min Wu, Ph.D., principal scientist. “There is a substantial need in oncology for preclinical models that better replicate human cancer. The field is watching closely to see how biomarkers discovered in these new models translate into humans.”

Noninvasive Disease Detection

According to Jack Leonard, president of technology commercialization at febit, the ability to assay all known miRNAs is key to finding valuable cancer biomarkers. “A readily apparent disadvantage for a single biomarker is low sensitivity. One of the best known biomarkers is prostate-specific antigen (PSA). When PSA is present at a typical threshold value of 4 ng/mL of blood, your sensitivity is only 20 percent—which is clearly not a good number because you are only detecting 20 percent of the cancers that are present.”

Historically, Dr. Leonard noted that research has moved forward with many people working on problems independently, typically with one laboratory working with a particular biomarker, while another lab might be working on the same biomarker with a different protocol.

“One problem is that biomarker discovery was not sufficiently standardized, and different laboratories were using different methods,” he explained. “We’ve created an automated approach applying a microfluidic polymerase extension assay (MPEA) for all known human miRNAs and controlling for all the nonbiological variables. We assay biomarkers and samples simultaneously, but hold the other things constant by using the same technology platform. This allows us to do large and well-controlled studies to identify the most informative miRNA signatures.”

Dr. Leonard said that febit’s noninvasive diagnostic assay was specifically designed for the integrated detection of a broad panel of diseases and is well suited for high sample throughput at low cost. “Our sensitivity and specificity for prostate cancer are greater than 95 percent.”

Dr. Leonard also explained the benefits of the Geniom RT Analyzer platform. “We have advantages over other miRNA-expression profiling techniques—the way we manufacture the biochips using light-directed oligonucleotide synthesis, we can turn around new designs quickly. Automation and flexibility are important features of Geniom technology, as this gives clinical researchers the reproducible performance they need to add new results to their growing database on their disease, and the ability to easily change content as more miRNAs are discovered.”

One of the other advantages of the platform is that samples can be collected with minimal discomfort—a blood draw is sufficient to isolate total RNA from the sample and hybridize miRNA onto the biochip. “We hope that this will eventually be used by doctors, but for right now it is more of a clinical research tool—it might be a number of years before this is used as a diagnostic platform.”

Jianfeng Xu, M.D., Dr.PH, professor at Wake Forest University School of Medicine, discussed three types of prostate cancer related to genetic variants that have been found from genome-wide association studies, including those associated with overall prostate cancer risk, aggressive prostate cancer risk, and higher baseline PSA levels.

There has been great progress in this field in terms of identifying the SNPs associated with cancer risk, he noted. In the past three years, for instance, 30 SNPs have been identified. And those 30 are consistently validated in studies of European descents.

While researchers, including Dr. Xu’s team, have identified multiple genetic variants associated with the risk of developing prostate cancer in the first place, until now there have been no genetic factors associated with disease aggressiveness. Based on existing evidence that some men are genetically predisposed to developing aggressive prostate cancer, the researchers hypothesized that inherited genetic variants exist that could be used as markers to identify these men at an early, curable stage of disease.

The researchers identified a genetic variant (rs4054823) that was associated with a 25% higher risk of developing aggressive disease. “A single variant with a moderate effect such as this is unlikely to be sufficient on its own at predicting risk for aggressive prostate cancer,” explained Dr. Xu. “But its identification is significant because it indicates that variants predisposing men to aggressive disease exist in the genome. Knowing your risk to prostate cancer is important. But knowing whether you likely develop lethal cancer versus indolent cancer is more important.”

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